Monitoring your case archival and purge process
View the completion of your archiving and purge jobs within a single view using the Log-Archival summary class and its associated log files. Alternatively, view the pr_metadata table, which holds all of the pyArchiveStatus and other information about all records that are processed by the three types of archival jobs.
Monitoring with the Log-Archival Summary class
Open the Log-ArchivalSummary class with the following procedure:- In the navigation pane of Dev Studio, click App.
- On the Classes tab, in the Search field, enter Log-ArchivalSummary, and then select the Log-ArchivalSummary class.
- Review the following columns to confirm the success of the archival process:
| Column | Description |
| Task | The name of the job running through the Job Scheduler. For more
information about the jobs used during a case archival and purge process,
see Case archiving and purging overview. This includes the following types of tasks:
|
| pyTaskEndTime | When the job finished. |
| pyCaseProcessed | The number of cases that the job successfully completed. |
| pyCasesUnsuccessful | The number of cases that the job failed to complete |
The Log-Archival summary class holds 365 days worth of entries before discarding old entries. Entries older than this number are purged.
To specify how long to maintain older entries in the activity, use the TrimLog activity.
- In the navigation pane of Dev Studio, click .
- In the Setting Purpose column, click the filter icon and filter the column by entering TrimLog.
- Select TrimLog.
- Select .
- In the daysAgo field, enter the number of days that you want to hold Log-Archival class entries.
- Click Run.
Monitoring your archival progress using logs
Review the log entries for the archiving and purge jobs found in the
PegaRULES.log.
- Search for Archival-CaseCrawler,
Archival-CaseCopier,
Archival-Purger, or
Archival-Indexer to view detailed log messages
for the respective events of each job.
- The
PegaRULES.logfile lists five cases for each batch that you define in the archive setting dataarchival/batchSize, to present a sample of where Pega Platform is archiving eligible cases in your backlog.
- The log message Final status for file <filepath> is confirmation of completion of an archival job, with the file path of the corresponding .zip archive file in Pega Cloud File Storage.
- The
- Search for the ERROR and
INFO_FORCED log levels for archiving and purge
jobs to find failures during your archival and purge process. Failures use the
following format to present where the archiving and purge process did not
succeed:
<Log level> - <timestamp> <Archival-CaseCrawler, Archival-CaseCopier, Archival-Purger, or Archival-Indexer job> : <CaseType>-<CaseTypeID>
Monitoring your progress using queries to the pr_metadata table
Use the Query Runner to run an SQL statement on the pr_metadata table. For more information about Query Runner, see Running SQL queries on Pega Cloud.
The return of the SQL query contains the value for pyArchiveStatus. The following figure shows when the status occurs during the archival process:
| Archival process step | pyArchiveStatus | Description |
| 1. | Archive-Ready | (Status occurs after the Crawler steps of the
pyPegaArchiver job.) The record is pending to go through the Copier step of the pyPegaArchiver job. |
| 2A. | Archived | (Status occurs after the pyPegaArchiver job.)
The record is copied to Pega Cloud File Storage. |
| 2B. | Archive-External | (Status occurs after the pyPegaArchiver job.)
The record is an external attachment, and reference is copied to Pega Cloud File Storage. |
| 2C. | Archive-Shared | (Status occurs after the pyPegaArchiver job.)
The record is shared between cases, and may not be eligible for an archival process. |
| 2D. | Archive-Failed | (Status occurs after the pyPegaArchiver job.)
The archival process failed. |
| 3A. | Pending-Purge | (Status occurs after the pyPegaIndexer job.)
The record has been indexed into Elasticsearch and is pending to go through the purge process. |
| 3B. | Indexing-Failed | (Status occurs after the pyPegaIndexer job.)
The indexing of the record into Elasticsearch failed. |
| 4. | <empty pr_metadata table> | (Empty tables occur after the pyPegaPurger job.)
The record has been purged from the Pega database. |
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